Method and system removing fluorescence and other slowly varying baseline in Raman spectra

ABSTRACT

A data set processing method for Raman spectroscopy systems using tunable lasers and multielement spectrometers compiles the spectral data set into an array and then estimates the background component, which is usually dominated by sample and optical train fluorescence, detector array dark current signal, fixed-pattern signal, and stray-light signals either modulated or non-modulated by in-path optics. This estimate is used as a baseline correction to the spectral data set to thereby isolate the sample&#39;s Raman response.

RELATED APPLICATIONS

This application claims the benefit under 35 USC 119(e) of U.S.Provisional Application No. 60/654,855, filed on Feb. 18, 2005, which isincorporated herein by reference in its entirety.

BACKGROUND OF THE INVENTION

Raman spectroscopy is similar to infrared (IR), including near infrared(NIR), spectroscopy but has several advantages. The Raman effect ishighly sensitive to slight differences in chemical composition andcrystallographic structure. These characteristics make it very usefulfor substance identification such as the investigation of illegal drugsand other unknown substances as it enables distinguishing between legaland illicit compounds, even when the compounds have a similar elementalcomposition. In other applications, taggants, with known Ramansignatures, are used as markers for goods.

Raman spectroscopy has additional advantages. When using IR spectroscopyon aqueous samples, a large proportion of the vibrational spectrum canbe masked by the intense water signal or absorbed by the water. Thistypically necessitates sample preparation. In contrast, with Ramanspectroscopy, aqueous samples can be more readily analyzed since theRaman signature from water is relatively weak. Also, because of the poorwater signature, Raman spectroscopy is often useful when analyzingbiological and inorganic systems, and in studies dealing with waterpollution problems.

Raman scattering may be regarded as an inelastic collision of anincident photon with a molecule. The photon may be scatteredelastically, that is without any change in its wavelength, and this isknown as Rayleigh scattering. Conversely the photon may be scatteredinelastically resulting in the Raman effect.

There are two types of Raman transitions. Upon collision with amolecule, a photon may lose some of its energy. This is known as Stokesradiation. Or, the photon may gain some energy—this is known asanti-Stokes radiation. This happens when the incident photon isscattered by a vibrationally excited molecule—there is gain in energyand the scattered photon has a higher frequency.

When viewed with a spectrometer, both the Stokes and anti-Stokesradiation are composed of lines that correspond to molecular vibrationsof the substance under investigation. Each compound has its own uniqueRaman spectrum, which can be used as a fingerprint for identification.

The Raman process is non linear. When incident photons have a lowintensity, only spontaneous Raman scattering will occur. As theintensity of the incident light wave is increased, an enhancement of thescattered Raman field can occur in which initially scattered Stokesphotons can promote further scattering of additional incident photons.With this process, the Stokes field grows exponentially and is known asstimulated Raman scattering (SRS).

One disadvantage associated with Raman spectroscopy, however, isfluorescence Fluorescence arising from molecular relaxation radiationhas been the major obstacle for Raman spectroscopy. In many cases, thefluorescence response of a sample can overwhelm the typically muchweaker Raman signature. This can make detection of small peaks in theRaman signature difficult. Some data processing techniques to thefluorescence baseline corrections are not effective since they usuallydo not provide sufficient discrimination between the fluorescentbaseline and the Raman spectra.

Often, fluorescence can be mitigated by moving to a longer wavelengthexcitation. This can create other problems, however. Another solution tothe fluorescence response is using excitation signals at multiplewavelengths. This is sometimes referred to as Shifted Excitation RamanDifference Spectroscopy (SERDS). Specifically, in the past others havesuggested to use excitation signals that comprise two excitationwavelengths, generated by two different single frequency lasers. Then,by looking at the spectra generated by each of the wavelengths, thefluorescence signal can be identified since the fluorescence signalchanges very little with excitation wavelength, whereas the Raman signalchanges as a direct function of the excitation wavelength. In thesimplest example, the spectrum at the two wavelengths is subtracted toremove the highly stationary fluorescence response. Recently, thissolution has been further enhanced by using a continuously tunablesemiconductor diode laser system. In these systems, the spectralresponse of the sample is monitored as the excitation signals wavelengthis scanned over a scan range. By looking at how the spectral responsechanges with the tuning of the excitation signal and how it does notchange, the Raman response can be separated from the fluorescenceresponse of the sample.

SUMMARY OF THE INVENTION

Using a continuously tunable or a small step-wise tunable laser sourcein combination with a multi element detector system such as agrating-based spectrometer with a linear detector array, yields a largespectral data set compromised of each detector elements sampled responseat each wavelength in the tunable laser's scan range. This spectral dataset must be processed to remove noise, such as the fluorescence responseand thereby isolate the Raman response.

The present invention concerns a data set processing method for Ramanspectroscopy systems using tunable lasers and multielementspectrometers. One example of such a spectrometer is the conventionalgrating-based dispersive spectrometer in which a grating is used todisperse the spectrum onto a linear detector array. Other examples arethe tunable multiorder multichannel Raman spectrometers described inU.S. patent application Ser. No. 10/967,075, filed Oct. 15, 2004, byXiaomei Wang, entitled Multi Channel Raman Spectrometer System andMethod, which application is incorporated herein in its entirety by thisreference.

The invention comprises compiling the spectral data set into an arrayand then estimating the background component, which is usually dominatedby sample and optical train fluorescence, detector array dark currentsignal, fixed-pattern signal, and stray-light signals either modulatedor non-modulated by in-path optics. This estimate is used as a baselinecorrection to the spectral data set to thereby isolate the sample'sRaman response.

In principle, the invention is applicable in any tunable laser basedRaman spectrometers, where fluorescence is present. By effectivelyremoving the fluorescence and any other non-Raman background, theprocessed spectrum reflects the true substance properties. This producesmuch higher identification fidelity when identifying the substancesagainst libraries.

The theory behind this invention is that the spectra of fluorescence andsome other baseline background, such as sample heat radiation, aredescribed in absolute wavelength (frequency) domain, and fullycharacterized by the detection wavelength only. They usually have muchbroader peaks than Raman spectral peaks. The Raman spectra, on the otherhand, depend on the Raman shift, which is related to both excitation anddetection wavelength.

In general, according to one aspect, the invention features a method ofprocessing spectral data from a Raman spectroscopy system. Thisspectroscopy system comprises a source for illuminating a sample at aplurality of wavelengths within a scan band. In one example, the sourceis a tunable laser. A spectrometer is also provided. It includes anarray of detection elements. One example is a linear detector array suchas a CCD or InGaAs type detector arrays. The array detects the spectralresponse of the sample as the source is illuminated at the plurality ofwavelengths. The method comprises compiling a spectral data setincluding the responses of the detection elements for each of theplurality of wavelengths. The responses are then characterized based onlevels of change in the response with changes in the wavelength of theillumination. Then, a baseline is determined from the responses, and thespectral data set is corrected using the determined baseline.

In specific embodiments, the spectrometer comprises a dispersive elementsuch as a grating for dispersing the spectral response over the array ofdetection elements. In further examples, the step of compiling thespectral data set comprises placing the spectral data set in an array ofresponses for each of the detection elements for each of the pluralityof wavelengths. The step of characterizing responses comprisinganalyzing responses of each of the detection elements with changes inthe wavelength of illumination. One method of characterizing thesechanges is to calculate a standard deviation in the responses withchanges and wavelength.

The baseline is then determined typically by excluding the responses ofthe detection elements that exhibit a large change in standarddeviation. A best fit polynomial is used in one example to characterizethe baseline. This baseline is then subtracted from the spectral dataset.

In general, according to another aspect, the invention features a Ramanspectroscopy system. This system comprises a source for illuminating asample at a plurality of wavelengths within a scan band. A spectrometerincludes an array of detection elements for detecting a spectralresponse of the sample in response to illumination by the source at theplurality of wavelengths. A system controller controls the source andreceives the responses from the detection elements of the spectrometer.The system controller processes the spectral data to determine a Ramanresponse of the sample. This is accomplished by compiling a spectraldata set including the responses of the detection elements for each ofthe plurality of wavelengths and characterizing the responses of thedetection elements based on levels of change in the response withchanges in the wavelength of the illumination. Based on this analysis, abaseline is determined for the responses, and the spectral data set isthen corrected based on the response to the determined baseline.

The above and other features of the invention including various noveldetails of construction and combinations of parts, and other advantages,will now be more particularly described with reference to theaccompanying drawings and pointed out in the claims. It will beunderstood that the particular method and device embodying the inventionare shown by way of illustration and not as a limitation of theinvention. The principles and features of this invention may be employedin various and numerous embodiments without departing from the scope ofthe invention.

BRIEF DESCRIPTION OF THE DRAWINGS

In the accompanying drawings, reference characters refer to the sameparts throughout the different views. The drawings are not necessarilyto scale; emphasis has instead been placed upon illustrating theprinciples of the invention. Of the drawings:

FIG. 1 is a schematic diagram illustrating a Raman spectroscopy systemto which the present invention is applicable;

FIG. 2 is a flow diagram illustrating a method for processing a spectraldata from a Raman spectroscopy system;

FIG. 3 is plot of normalized response as a function of shift inwavenumbers (cm −1) for a Raman spectrum of potassium cyanide (KCN) witha Gaussian-like fluorescence baseline; and

FIG. 4 is plot of normalized response as a function of shift inwavenumbers (cm −1) for a Raman spectrum of acetaminophen.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

FIG. 1 illustrates a spectroscopy system to which the present inventionis applicable. Specifically, it comprises a source 110 for generating atunable wavelength illuminating beam 112 for irradiating the sample 10at a plurality of wavelengths λ₁, λ₂, λ_(m). Typically, the source 100is a tunable laser.

The illumination of the sample 110 by the laser beam 112 generates aresponse 114. Typically this response is a combination of thefluorescence response and the Raman response of the sample 10.

In order to resolve the spectral response of the sample 10, aspectrometer 120 is used. As a general example, the spectrometercomprises collection optics 122 that collect light from the sample 10and direct it to a dispersive element 124. In the typical example, thedispersive element 124 is a grating such as a standard line grating or aholographic grating.

The dispersive element 124 disperses the spectrum of the light 114 fromthe sample 10 in order to determine the spectral response of the sample10. In the specific example, grating optics 126 is used to form thespectral image on the linear detector array 128. In the preferredembodiment, this is a linear detector array 128 comprises elements i=1,2, . . . n. Often n is greater than 10 and typically greater than 32.

A system controller 150 is used to control the tunable laser 110 andspecifically control its wavelength λ. The system controller 150 alsoreceives the responses of the detection elements i=1, 2, . . . n fromthe detector array 128.

According to the present invention, the system controller analyzes thespectral data from the detector array 128 in combination with thewavelength of the tunable laser 110 in order to determine the Ramanspectral response of the sample 10.

FIG. 2 shows the baseline estimation method according to the principlesof the present invention.

The detected signal at the detector array 128 can be written as:Iij=Ii(fluorescence)+Ii(dark current)+Ii(sample heating)+Iij(Ramansignal), where i=1,2, . . . , n, represents each detector and j=1, 2, .. . , m, each step wise tuning point of the laser 110 or dataacquisition point in a continuously tuning mode of the laser.

In one example, the scan band of the laser 110 is between 1 and 15nanometers. In a preferred embodiment, the scan band is between 2 and 5nanometers. The spectral responses of the detector array 128 arecollected at more than 5 different wavelengths (m>5) within the scanband. In the preferred embodiment, spectral responses of the detectorarray 128 are collected at more than 12, preferably more than 20,different wavelengths within the scan band.

The responses of the detection elements at each of the wavelengths λ₁ .. . λ_(m) are compiled into a spectral data set 210. Specifically, thespectral data set 210 is formed into an array of responses that holdseach of the detection elements response for each of the plurality ofwavelengths.

Then, in step 212, the original spectral data set 210 is sorted so thatthe detected responses are in ascending order for each detectorindividually. It produces a sorted array 214.

From the sorted array, the mean and standard deviation are calculatedfor each of the detectors i=1 to n in step 216. In the currentembodiment, this is performed for a selected number m1 of data points ora number of data points determined by a user selected criterion for eachdetector. This criterion can be either fixed or dynamically variablebased on the data set. This process produces an array of calculated meanand standard deviation values 218.

In step 220, the standard deviation and mean array 218 is sorted andonly a fixed number n1 or a number of detectors with the standarddeviation less than a threshold times the lowest standard deviation,among the detectors, are selected to produce array 222. In short, theresponses of the detector elements that exhibited the smaller changes,have lower standard deviation as a function of changes in wavelength,are identified. The responses of these detector elements that exhibitedthe lowest change are then used to calculate a polynomial fit as afunction of detector wavelengths in step 224. This produces a polynomialarray 226.

In one embodiment, the fitting results are analyzed and any outliers areremoved. The polynomials are refit and the baseline is thenre-calculated. This produces the polynomial array 226. This baseline isthen subtracted in step 228. This produces the corrected Raman spectralresponse array 330.

Simulations of the method's performance were performed with fourdifferent slow varying baselines: linear, parabolic, slow and fastGaussian. Due to the nature of the multiorder multichannel detection ofthe tunable multiorder multichannel Raman spectrometers as described inU.S. patent application Ser. No. 10/967,075, a typical expected detectedsignal with fluorescent baseline is illustrated in FIG. 3, where theRaman spectrum is from Potassium Cyanide and the baseline 310 is assumedto be in a fast Gaussian form. A stair-like baseline presents thediscrimination between Raman signal and fluorescence background.

In the simulation, we used the following parameters:

1. Number of detectors: n=64

2. Number of tuning steps: m=41

3. Number of data points used for standard deviation and calculation:m1=10

4. Number of detectors used for baseline estimation: n1=30

Reference 312 illustrated the baseline corrected response of KCN with asingle peak.

FIG. 4 shows the raw response 310 and the baseline corrected Ramanresponse 312 for over-the-counter acetaminophen.

While this invention has been particularly shown and described withreferences to preferred embodiments thereof, it will be understood bythose skilled in the art that various changes in form and details may bemade therein without departing from the scope of the inventionencompassed by the appended claims.

1. A method of processing spectral data from a Raman spectroscopysystem, comprising: a source for illuminating a sample at a plurality ofwavelengths within a scan band; and a spectrometer including an array ofdetection elements for detecting a spectral response of the sample inresponse to illumination by the source at the plurality of wavelengths;wherein the method comprises: compiling a spectral data set includingthe responses of the detection elements for each of the plurality ofwavelengths; characterizing the responses of the detection elementsbased on levels of change in the responses with changes in thewavelength of the illumination; determining a baseline from theresponses; and correcting the spectral data set using the determinedbaseline.
 2. A method as claimed in claim 1, wherein the spectrometer ofthe Raman spectroscopy system further comprises a dispersive element ofdispersing the spectral response over the array of detection elements.3. A method as claimed in claim 1, wherein the step of compiling thespectral data set comprises placing the spectral data set in an array ofresponses for each of the detection elements for each of the pluralityof wavelengths.
 4. A method as claimed in claim 1, wherein the step ofcharacterizing the responses comprises analyzing the responses of eachdetection elements for changes with changes in the wavelength of theillumination.
 5. A method as claimed in claim 1, wherein the step ofcharacterizing the responses comprises analyzing the responses of eachdetection element based on the deviation in the responses with changesin the wavelength of the illumination.
 6. A method as claimed in claim1, wherein the step of determining the baseline comprising determining abest fit polynomial.
 7. A method as claimed in claim 1, wherein the stepof correcting the spectral data set comprises subtracting the baselinefrom the spectral data set.
 8. A Raman spectroscopy system, comprising:a source for illuminating a sample at a plurality of wavelengths withina scan band; a spectrometer including an array of detection elements fordetecting a spectral response of the sample in response to illuminationby the source at the plurality of wavelengths; and a system controllerfor controlling the source and receiving responses of the detectionelements of the spectrometer, the system controller processing thespectral data to determine a Raman response of the sample by compiling aspectral data set including the responses of detection elements for eachof the plurality of wavelengths, characterizing the responses of thedetection elements based on levels of change in the responses withchanges in the wavelength of the illumination, determining a baselinefrom the responses, and correcting the spectral data set in response tothe determined baseline.
 9. A system as claimed in claim 8, wherein thespectrometer of the Raman spectroscopy system further comprises adispersive element of dispersing the spectral response over the array ofdetection elements.
 10. A system as claimed in claim 8, wherein thesource comprises a tunable laser.
 11. A system as claimed in claim 8,wherein the system controller compiles the spectral data set by placingthe spectral data set in an array with responses for each of thedetection elements for each of the plurality of wavelengths.
 12. Asystem as claimed in claim 8, wherein the system controllercharacterizes the responses by analyzing the responses of each detectionelement for changes with changes in the wavelength of the illumination.13. A system as claimed in claim 8, wherein the system controllercharacterizes the responses by analyzing the responses of each detectionelement based on the deviation in the responses with changes in thewavelength of the illumination.
 14. A system as claimed in claim 8,wherein the system controller determines the baseline by determining abest fit polynomial.
 15. A system as claimed in claim 8, wherein thestep of correcting the spectral data set comprises subtracting thebaseline from the spectral data set.